Nextflow Registry | nf-core/catpack/reads@0.0.0-6c4ed3a

nf-core/catpack/reads @ 0.0.0-6c4ed3a

Taxonomic classification plus read-based abundance estimation from long DNA sequences and metagenome assembled genomes (e.g. contigs, MAGs / bins).

Latest version: 0.0.0-6c4ed3a

Total downloads: 9

Source: nf-core/modules

Authors: @jfy133

Maintainers: @jfy133

Taxonomic classification plus read-based abundance estimation from long DNA sequences and metagenome assembled genomes (e.g. contigs, MAGs / bins).

Add the following snippet to your workflow script to include this module.

include { CATPACK_READS } from 'nf-core/catpack/reads'

MIT License

Process

`Name`	`CATPACK_READS`

Input 13 channels

#1 tuple

`meta` map	Groovy Map containing sample information e.g. `[ id:'sample1', single_end:false ]`
`reads` file	One or a pair of nucleotide FASTQ files (R1, R2) containing reads for mapping. Interleaved not supported. `*.{fastq,fq,fastq.gz,fq.gz}`

#2 tuple

`meta2` map	Groovy Map containing sample information e.g. `[ id:'sample1', single_end:false ]`
`contigs` file	A nucleotide FASTA file containing long DNA sequences such as contigs. Optional if `bins` supplied. `*.{fasta,fna,fa,fas}`

#3 tuple

`meta3` map	Groovy Map containing sample information e.g. `[ id:'sample1', single_end:false ]`
`database` directory	Directory containing CAT_pack database files (e.g. output from CAT_pack prepare) `*/`

#4 tuple

`meta4` map	Groovy Map containing sample information e.g. `[ id:'sample1', single_end:false ]`
`taxonomy` directory	Directory containing CAT_pack taxonomy files (e.g. output from CAT_pack prepare) `*/`

#5 tuple

`meta5` map	Groovy Map containing sample information e.g. `[ id:'sample1', single_end:false ]`
`bins` file	One or more nucleotide FASTA file containing binned long DNA sequences. Optional if `contigs` supplied. Note: if you supply bins, you must also give the `-s <fasta suffix>` corresponding to the file extension of the bins via `ext.args` `*.{fasta,fna,fa,fas}`

`mode` string	Mode of operation of CAT_pack reads, "mcr": integrate annotations from MAGs (bins), contigs, and reads; "cr": integrate annotations from contigs and reads; "mr": integrate annotations from MAGs (bins) and reads. `mcr\|cr\|mr`

#7 tuple

`meta6` map	Groovy Map containing sample information e.g. `[ id:'sample1', single_end:false ]`
`bam_aligned` file	Optional pre-aligned and sorted reads mapped against contigs/bins. `*.bam`

#8 tuple

`meta7` map	Groovy Map containing sample information e.g. `[ id:'sample1', single_end:false ]`
`bam_unaligned` file	Optional sorted unaligned reads from mapping against contigs/bins. `*.bam`

#9 tuple

`meta8` map	Groovy Map containing sample information e.g. `[ id:'sample1', single_end:false ]`
`contig2classification` file	Optional TSV file with per-contig hit stats and assignment justification information `*.contig2classification.txt`

#10 tuple

`meta9` map	Groovy Map containing sample information e.g. `[ id:'sample1', single_end:false ]`
`bin2classification` file	Optional TSV file with per-bin hit stats and assignment justification information `*.bin2classification.txt`

#11 tuple

`meta10` map	Groovy Map containing sample information e.g. `[ id:'sample1', single_end:false ]`
`unclassified2classification` file	Optional TSV file with pre-made CAT_pack reads unmapped2classification.txt file information `*.txt`

#12 tuple

`meta11` map	Groovy Map containing sample information e.g. `[ id:'sample1', single_end:false ]`
`proteins` directory	Optional pre predicted-made proteins FASTA `*.{fasta,faa,fa,fas}`

#13 tuple